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ICML
2004
IEEE
14 years 5 months ago
Variational methods for the Dirichlet process
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
David M. Blei, Michael I. Jordan
UAI
2001
13 years 5 months ago
Expectation Propagation for approximate Bayesian inference
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
Thomas P. Minka
ICML
2007
IEEE
14 years 5 months ago
Incremental Bayesian networks for structure prediction
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
Ivan Titov, James Henderson
CVPR
2004
IEEE
14 years 6 months ago
Collaborative Tracking of Multiple Targets
Coalescence, meaning the tracker associates more than one trajectories to some targets while loses track for others, is a challenging problem for visual tracking of multiple targe...
Ting Yu, Ying Wu